1. Field of the Invention
The present invention relates to an improved data processing system and, in particular, to a method and apparatus for enhancing network services. Still more particularly, the present invention provides a method and system for configuration and allocation of networked resources.
2. Description of Related Art
In a highly distributed computational system, the applications that perform operations for a given network service may be dispersed on physical devices throughout the network. Applications on other physical devices that desire access to the given network service must be provided with information on the manner in which a connection with the network service can be obtained.
A complete inventory of available networked resources may be distributed throughout the system. In a system in which networked resources are continually going online and offline, a significant amount of attention must be given to dispersing information about the availability of networked resources and their location, both physical location and logical location or organization.
In any given network, the demand for networked resources fluctuates over time. In a highly distributed computing system, all of the computer platforms may have varying needs for networked resources, thereby creating a very dynamic environment for managing networked resources.
Generally, network management software within the distributed computing system satisfies the demand for networked resources using some type of load balancing such that all service requesters eventually get access to the requested service. It is sometimes critical to load balance the demand for services by distributing the request workload across the entire system in order to ensure fair access.
When multiple concurrent access is needed to satisfy the request workload, most existing systems only rely on some internal metrics without any knowledge of the outside environment. For example, a system may monitor its number of concurrent client connections to ensure that the number does not exceed a maximum threshold. Many current load balancing implementations are based on complex algorithms that apply only to a specific configuration.
In order for a load balancing mechanism to operate successfully using internal metrics, a mathematical model of the expected behavior of the system must closely approximate the actual demands that are placed on the system. In a system in which the behavior of its devices and applications can be relatively easily monitored, an accurate model might be easily devised. However, in a highly distributed environment, the load demand can vary greatly, and it is difficult to devise a load balancing mechanism based on internally derived metrics.
Therefore, it would be advantageous to provide a method and system for automatically load balancing the demand on networked resources based on user-driven demand.